Draft version January 16, 2014Preprint typeset using LATEX style emulateapj v. 12/16/11

THE TENTH DATA RELEASE OF THE SLOAN DIGITAL SKY SURVEY: FIRST SPECTROSCOPIC DATAFROM THE SDSS-III APACHE POINT OBSERVATORY GALACTIC EVOLUTION EXPERIMENT

Christopher P. Ahn1, Rachael Alexandroff2, Carlos Allende Prieto3,4, Friedrich Anders5,6,

Scott F. Anderson7, Timothy Anderton1, Brett H. Andrews8, Eric Aubourg9, Stephen Bailey10,Fabienne A. Bastien11, Julian E. Bautista9, Timothy C. Beers12,13, Alessandra Beifiori14, Chad F. Bender15,16

Andreas A. Berlind11, Florian Beutler10, Vaishali Bhardwaj7,10, Jonathan C. Bird11, Dmitry Bizyaev17,18,Cullen H. Blake19, Michael R. Blanton20, Michael Blomqvist21, John J. Bochanski22,7, Adam S. Bolton1,

Arnaud Borde23, Jo Bovy24,25, Alaina Shelden Bradley17, W. N. Brandt15,26, Dorothee Brauer5, J. Brinkmann17,Joel R. Brownstein1, Nicolas G. Busca9, William Carithers10, Joleen K. Carlberg27, Aurelio R. Carnero28,29,

Michael A. Carr30, Cristina Chiappini5,29, S. Drew Chojnowski31, Chia-Hsun Chuang32, Johan Comparat33,Justin R. Crepp34, Stefano Cristiani35,36, Rupert A.C. Croft37, Antonio J. Cuesta38, Katia Cunha28,39,Luiz N. da Costa28,29, Kyle S. Dawson1, Nathan De Lee11, Janice D. R. Dean31, Timothee Delubac23,

Rohit Deshpande15,16, Saurav Dhital40,11, Anne Ealet41, Garrett L. Ebelke17,18, Edward M. Edmondson42,Daniel J. Eisenstein43, Courtney R. Epstein8, Stephanie Escoffier41, Massimiliano Esposito3,4,Michael L. Evans7, D. Fabbian3, Xiaohui Fan39, Ginevra Favole32, Bruno Femena Castella3,4,

Emma Fernandez Alvar3,4, Diane Feuillet18, Nurten Filiz Ak15,26,44, Hayley Finley45, Scott W. Fleming15,16,Andreu Font-Ribera46,10, Peter M. Frinchaboy47, J. G. Galbraith-Frew1, D. A. Garca-Hernandez3,4,

Ana E. Garca Perez31, Jian Ge48, R. Genova-Santos3,4, Bruce A. Gillespie2,17, Leo Girardi49,29,Jonay I. Gonzalez Hernandez3, J. Richard Gott, III30, James E. Gunn30, Hong Guo1, Samuel Halverson15,

Paul Harding50, David W. Harris1, Sten Hasselquist18, Suzanne L. Hawley7, Michael Hayden18,Frederick R. Hearty31, Artemio Herrero Davo3,4, Shirley Ho37, David W. Hogg20, Jon A. Holtzman18,

Klaus Honscheid51,52, Joseph Huehnerhoff17, Inese I. Ivans1, Kelly M. Jackson47,53, Peng Jiang54,48,Jennifer A. Johnson8,52, K. Kinemuchi17,18, David Kirkby21, Mark A. Klaene17, Jean-Paul Kneib55,33,

Lars Koesterke56, Ting-Wen Lan2, Dustin Lang37, Jean-Marc Le Goff23, Alexie Leauthaud57, Khee-Gan Lee58,Young Sun Lee18, Daniel C. Long17,18, Craig P. Loomis30, Sara Lucatello49, Robert H. Lupton30, Bo Ma48,

Claude E. Mack III11, Suvrath Mahadevan15,16, Marcio A. G. Maia28,29, Steven R. Majewski31,Elena Malanushenko17,18, Viktor Malanushenko17,18, A. Manchado3,4, Marc Manera42, Claudia Maraston42,

Daniel Margala21, Sarah L. Martell59, Karen L. Masters42, Cameron K. McBride43, Ian D. McGreer39,Richard G. McMahon60,61, Brice Menard2,57,62, Sz. Meszaros3,4, Jordi Miralda-Escude63,64, Hironao Miyatake30,

Antonio D. Montero-Dorta1, Francesco Montesano14, Surhud More57, Heather L. Morrison50, Demitri Muna8,Jeffrey A. Munn65, Adam D. Myers66, Duy Cuong Nguyen67, Robert C. Nichol42, David L. Nidever68,31,

Pasquier Noterdaeme45, Sebastian E. Nuza5, Julia E. OConnell47, Robert W. OConnell31, Ross OConnell37,Matthew D. Olmstead1, Daniel J. Oravetz17, Russell Owen7, Nikhil Padmanabhan38,

Nathalie Palanque-Delabrouille23, Kaike Pan17, John K. Parejko38, Prachi Parihar30, Isabelle Paris69,Joshua Pepper70,11, Will J. Percival42, Ignasi Perez-Rafols64,71, Helio Dotto Perottoni72,29,

Patrick Petitjean45, Matthew M. Pieri42, M. H. Pinsonneault8, Francisco Prada73,32,74,Adrian M. Price-Whelan75, M. Jordan Raddick2, Mubdi Rahman2, Rafael Rebolo3,76, Beth A. Reid10,25,

Jonathan C. Richards1, Rogerio Riffel77,29, Annie C. Robin78, H. J. Rocha-Pinto72,29, Constance M. Rockosi79,Natalie A. Roe10, Ashley J. Ross42, Nicholas P. Ross10, Graziano Rossi23, Arpita Roy15, J. A. Rubino-Martin3,4,

Cristiano G. Sabiu80, Ariel G. Sanchez14, Baslio Santiago77,29, Conor Sayres7, Ricardo P. Schiavon81,David J. Schlegel10, Katharine J. Schlesinger82, Sarah J. Schmidt8, Donald P. Schneider15,26,

Mathias Schultheis78, Kris Sellgren8, Hee-Jong Seo10, Yue Shen43,83, Matthew Shetrone84, Yiping Shu1,Audrey E. Simmons17, M. F. Skrutskie31, Anze Slosar85, Verne V. Smith12, Stephanie A. Snedden17,

Jennifer S. Sobeck86, Flavia Sobreira28,29, Keivan G. Stassun11,87, Matthias Steinmetz5, Michael A. Strauss30,88,Alina Streblyanska3,4, Nao Suzuki10, Molly E. C. Swanson43, Ryan C. Terrien15,16, Aniruddha R. Thakar2,

Daniel Thomas42, Benjamin A. Thompson47, Jeremy L. Tinker20, Rita Tojeiro42, Nicholas W. Troup31,Jan Vandenberg2, Mariana Vargas Magana37, Matteo Viel35,36, Nicole P. Vogt18, David A. Wake89,

Benjamin A. Weaver20, David H. Weinberg8, Benjamin J. Weiner39, Martin White90,10, Simon D.M. White91,John C. Wilson31, John P. Wisniewski92, W. M. Wood-Vasey93,88, Christophe Yeche23, Donald G. York94,

O. Zamora3,4, Gail Zasowski8,2, Idit Zehavi50, Gong-Bo Zhao42,95, Zheng Zheng1, Guangtun Zhu2

Draft version January 16, 2014

ABSTRACT

The Sloan Digital Sky Survey (SDSS) has been in operation since 2000 April. This paper presents thetenth public data release (DR10) from its current incarnation, SDSS-III. This data release includes thefirst spectroscopic data from the Apache Point Observatory Galaxy Evolution Experiment (APOGEE),along with spectroscopic data from the Baryon Oscillation Spectroscopic Survey (BOSS) taken through2012 July. The APOGEE instrument is a near-infrared R 22,500 300-fiber spectrograph covering1.5141.696 m. The APOGEE survey is studying the chemical abundances and radial velocities ofroughly 100,000 red giant star candidates in the bulge, bar, disk, and halo of the Milky Way. DR10includes 178,397 spectra of 57,454 stars, each typically observed three or more times, from APOGEE.Derived quantities from these spectra (radial velocities, effective temperatures, surface gravities, andmetallicities) are also included.

2

DR10 also roughly doubles the number of BOSS spectra over those included in the ninth data release.DR10 includes a total of 1,507,954 BOSS spectra, comprising 927,844 galaxy spectra; 182,009 quasarspectra; and 159,327 stellar spectra, selected over 6373.2 deg2.Keywords: AtlasesCatalogsSurveys

1. INTRODUCTION

1 Department of Physics and Astronomy, University of Utah,Salt Lake City, UT 84112, USA.

2 Center for Astrophysical Sciences, Department of Physicsand Astronomy, Johns Hopkins University, 3400 North CharlesStreet, Baltimore, MD 21218, USA.

3 Instituto de Astrofsica de Canarias (IAC), C/Va Lactea,s/n, E-38200, La Laguna, Tenerife, Spain.

4 Departamento de Astrofsica, Universidad de La Laguna,E-38206, La Laguna, Tenerife, Spain.

5 Leibniz-Institut fur Astrophysik Potsdam (AIP), An derSternwarte 16, D-14482 Potsdam, Germany.

6 Technische Universitat Dresden (TUD), Institut fur Kern-und Teilchenphysik, D-01062 Dresden, Germany.

7 Department of Astronomy, University of Washington, Box351580, Seattle, WA 98195, USA.

8 Department of Astronomy, Ohio State University, 140 West18th Avenue, Columbus, OH 43210, USA.

9 APC, University of Paris Diderot, CNRS/IN2P3,CEA/IRFU, Observatoire de Paris, Sorbonne Paris Cite,F-75205 Paris, France.

10 Lawrence Berkeley National Laboratory, One CyclotronRoad, Berkeley, CA 94720, USA.

11 Department of Physics and Astronomy, Vanderbilt Uni-versity, VU Station 1807, Nashville, TN 37235, USA.

12 National Optical Astronomy Observatory, 950 NorthCherry Avenue, Tucson, AZ, 85719, USA.

13 Department of Physics and Astronomy and JINA: JointInstitute for Nuclear Astrophysics, Michigan State University,East Lansing, MI 48824, USA.

14 Max-Planck-Institut fur Extraterrestrische Physik,Giessenbachstrae, D-85748 Garching, Germany.

15 Department of Astronomy and Astrophysics, 525 DaveyLaboratory, The Pennsylvania State University, UniversityPark, PA 16802, USA.

16 Center for Exoplanets and Habitable Worlds, 525 DaveyLaboratory, Pennsylvania State University, University Park, PA16802, USA.

17 Apache Point Observatory, P.O. Box 59, Sunspot, NM88349, USA.

18 Department of Astronomy, MSC 4500, New Mexico StateUniversity, P.O. Box 30001, Las Cruces, NM 88003, USA.

19 University of Pennsylvania, Department of Physics andAstronomy, 219 S. 33rd St., Philadelphia, PA 19104.

20 Center for Cosmology and Particle Physics, Department ofPhysics, New York University, 4 Washington Place, New York,NY 10003, USA.

21 Department of Physics and Astronomy, University ofCalifornia, Irvine, CA 92697, USA.

22 Haverford College, Department of Physics and Astronomy,370 Lancaster Avenue, Haverford, PA, 19041, USA.

23 CEA, Centre de Saclay, Irfu/SPP, F-91191 Gif-sur-Yvette,France.

24 Institute for Advanced Study, Einstein Drive, Princeton,NJ 08540, USA.

25 Hubble fellow.26 Institute for Gravitation and the Cosmos, The Pennsylva-

nia State University, University Park, PA 16802, USA.27 Department of Terrestrial Magnetism, Carnegie Institution

of Washington, 5241 Broad Branch Road, NW, Washington DC20015, USA.

28 Observatorio Nacional, Rua Gal. Jose Cristino 77, Rio deJaneiro, RJ - 20921-400, Brazil.

29 Laboratorio Interinstitucional de e-Astronomia, - LIneA,Rua Gal.Jose Cristino 77, Rio de Janeiro, RJ - 20921-400,Brazil.

30 Department of Astrophysical Sciences, Princeton Univer-sity, Princeton, NJ 08544, USA.

31 Department of Astronomy, University of Virginia, P.O.Box400325, Charlottesville, VA 22904-4325, USA.

The Sloan Digital Sky Survey (SDSS) has been in con-tinuous operation since 2000 April. It uses a dedicated

32 Instituto de Fsica Teorica, (UAM/CSIC), UniversidadAutonoma de Madrid, Cantoblanco, E-28049 Madrid, Spain.

33 Laboratoire dAstrophysique de Marseille, CNRS-Universite de Provence, 38 rue F. Joliot-Curie, F-13388Marseille cedex 13, France.

34 Department of Physics, 225 Nieuwland Science Hall, NotreDame, IN, 46556, USA.

35 INAF, Osservatorio Astronomico di Trieste, Via G. B.Tiepolo 11, I-34131 Trieste, Italy.

36 INFN/National Institute for Nuclear Physics, Via Valerio2, I-34127 Trieste, Italy.

37 Bruce and Astrid McWilliams Center for Cosmology,Department of Physics, Carnegie Mellon University, 5000Forbes Ave, Pittsburgh, PA 15213, USA.

38 Yale Center for Astronomy and Astrophysics, Yale Uni-versity, New Haven, CT, 06520, USA.

39 Steward Observatory, 933 North Cherry Avenue, Tucson,AZ 85721, USA.

40 Department of Physical Sciences, Embry-Riddle Aeronau-tical University, 600 South Clyde Morris Blvd., Daytona Beach,FL 32114, USA.

41 Centre de Physique des Particules de Marseille, Aix-Marseille Universite, CNRS/IN2P3, E-13288 Marseille, France.

42 Institute of Cosmology and Gravitation, Dennis SciamaBuilding, University of Portsmouth, Portsmouth, PO1 3FX,UK.

43 Harvard-Smithsonian Center for Astrophysics, HarvardUniversity, 60 Garden Street, Cambridge MA 02138, USA.

44 Faculty of Sciences, Department of Astronomy and SpaceSciences, Erciyes University, 38039 Kayseri, Turkey.

45 UPMC-CNRS, UMR7095, Institut dAstrophysique deParis, 98bis Boulevard Arago, F-75014, Paris, France.

46 Institute of Theoretical Physics, University of Zurich, 8057Zurich, Switzerland.

47 Department of Physics and Astronomy, Texas ChristianUniversity, 2800 South University Drive, Fort Worth, TX 76129,USA.

48 Department of Astronomy, University of Florida, BryantSpace Science Center, Gainesville, FL 32611-2055, USA.

49 INAF, Osservatorio Astronomico di Padova, VicolodellOsservatorio 5, I-35122 Padova, Italy.

50 Department of Astronomy, Case Western Reserve Univer-sity, Cleveland, OH 44106, USA.

51 Department of Physics, Ohio State University, Columbus,OH 43210, USA.

52 Center for Cosmology and Astro-Particle Physics, OhioState University, Columbus, OH 43210, USA.

53 Department of Physics, University of Texas-Dallas, Dallas,TX 75080, USA.

54 Key Laboratory for Research in Galaxies and Cosmol-ogy, University of Science and Technology of China, ChineseAcademy of Sciences, Hefei, Anhui, 230026, China.

55 Laboratoire dAstrophysique, Ecole PolytechniqueFederale de Lausanne (EPFL), Observatoire de Sauverny, 1290,Versoix, Switzerland.

56 Texas Advanced Computer Center, University of Texas,10100 Burnet Road (R8700), Austin, Texas 78758-4497, USA.

57 Kavli Institute for the Physics and Mathematics of theUniverse (Kavli IPMU, WPI), Todai Institutes for AdvancedStudy, The University of Tokyo, Kashiwa, 277-8583, Japan.

58 Max-Planck-Institut fur Astronomie, Konigstuhl 17,D-69117 Heidelberg, Germany.

59 Australian Astronomical Observatory, PO Box 915, NorthRyde NSW 1670, Australia.

60 Institute of Astronomy, University of Cambridge, Mading-ley Road, Cambridge CB3 0HA, UK.

61 Kavli Institute for Cosmology, University of Cambridge,Madingley Road, Cambridge CB3 0HA, UK.

SDSS DR10 3

wide-field 2.5-m telescope (Gunn et al. 2006) at ApachePoint Observatory (APO) in the Sacramento Mountainsin Southern New Mexico. It was originally instrumentedwith a wide-field imaging camera with an effective areaof 1.5 deg2 (Gunn et al. 1998), and a pair of double spec-trographs fed by 640 fibers (Smee et al. 2013). The ini-tial survey (York et al. 2000) carried out imaging in fivebroad bands (ugriz) (Fukugita et al. 1996) to a depth

62 Alfred P. Sloan fellow.63 Institucio Catalana de Recerca i Estudis Avancats,

Barcelona E-08010, Spain.64 Institut de Ciencies del Cosmos, Universitat de

Barcelona/IEEC, Barcelona E-08028, Spain.65 US Naval Observatory, Flagstaff Station, 10391 West

Naval Observatory Road, Flagstaff, AZ 86001-8521, USA.66 Department of Physics and Astronomy, University of

Wyoming, Laramie, WY 82071, USA.67 Dunlap Institute for Astronomy and Astrophysics, Uni-

versity of Toronto, Toronto, ON, M5S 3H4, Canada.68 Dept. of Astronomy, University of Michigan, Ann Arbor,

MI, 48104, USA.69 Departamento de Astronoma, Universidad de Chile,

Casilla 36-D, Santiago, Chile.70 Department of Physics, Lehigh University, 16 Memorial

Drive East, Bethlehem, PA 18015, USA.71 Departament dAstronomia i Meteorologia, Facultat de

Fsica, Universitat de Barcelona, E-08028 Barcelona, Spain.72 Federal do Rio de Janeiro, Observatorio do Valongo,

Ladeira do Pedro Antonio 43, 20080-090 Rio de Janeiro, Brazil.73 Campus of International Excellence UAM+CSIC, Canto-

blanco, E-28049 Madrid, Spain.74 Instituto de Astrofsica de Andaluca (CSIC), Glorieta de

la Astronoma, E-18080 Granada, Spain.75 Department of Astronomy, Columbia University, New

York, NY 10027, USA.76 Consejo Superior Investigaciones Cientficas, 28006

Madrid, Spain.77 Instituto de Fsica, UFRGS, Caixa Postal 15051, Porto

Alegre, RS - 91501-970, Brazil.78 Universite de Franche-Comte, Institut Utinam, UMR

CNRS 6213, OSU Theta, Besancon, F-25010, France.79 UCO/Lick Observatory, University of California, Santa

Cruz, 1156 High Street, Santa Cruz, CA 95064, USA.80 School of Physics, Korea Institute for Advanced Study, 85

Hoegiro, Dongdaemun-gu, Seoul 130-722, Republic of Korea.81 Astrophysics Research Institute, Liverpool John Moores

University, IC2, Liverpool Science Park 146 Brownlow HillLiverpool L3 5RF United Kingdom.

82 Research School of Astronomy and Astrophysics, Aus-tralian National University, Weston Creek, ACT, 2611,Australia.

83 Observatories of the Carnegie Institution of Washington,813 Santa Barbara Street, Pasadena, CA 91101, USA.

84 University of Texas, Hobby-Eberly Telescope, 32 FowlkesRd, McDonald Observatory, TX 79734-3005, USA.

85 Brookhaven National Laboratory, Bldg 510, Upton, NY11973, USA.

86 Department of Astronomy and Astrophysics and JINA,University of Chicago, Chicago, IL 60637, USA.

87 Department of Physics, Fisk University, 1000 17th AvenueNorth, Nashville, TN 37208, USA.

88 Corresponding authors.89 Department of Astronomy, University of Wisconsin-

Madison, 475 North Charter Street, Madison WI 53703, USA.90 Department of Physics, University of California, Berkeley,

CA 94720, USA.91 Max-Planck Institute for Astrophysics, Karl-

SchwarzschildStr 1, D-85748 Garching, Germany.92 H.L. Dodge Department of Physics and Astronomy,

University of Oklahoma, Norman, OK 73019, USA.93 PITT PACC, Department of Physics and Astronomy,

University of Pittsburgh, Pittsburgh, PA 15260, USA.94 Department of Astronomy and Astrophysics and the

Enrico Fermi Institute, University of Chicago, 5640 South EllisAvenue, Chicago, IL 60637, USA.

95 National Astronomy Observatories, Chinese Academy of

of r 22.5 mag over 11,663 deg2 of high-latitude sky,and spectroscopy of 1.6 million galaxy, quasar, and stel-lar targets over 9380 deg2. The resulting images werecalibrated astrometrically (Pier et al. 2003) and photo-metrically (Ivezic et al. 2004; Tucker et al. 2006; Pad-manabhan et al. 2008), and the properties of the de-tected objects were measured (Lupton et al. 2001). Thespectra were calibrated and redshifts and classificationsdetermined (Bolton et al. 2012). The data have been re-leased publicly in a series of roughly annual data releases(Stoughton et al. 2002; Abazajian et al. 2003, 2004, 2005;Adelman-McCarthy et al. 2006, 2007, 2008; Abazajianet al. 2009; hereafter EDR, DR1, DR2, DR3, DR4, DR5,DR6, DR7, respectively) as the project went through twofunding phases, termed SDSS-I (20002005) and SDSS-II(20052008).

In 2008, the SDSS entered a new phase, designatedSDSS-III (Eisenstein et al. 2011), in which it is currentlyoperating. SDSS-III has four components. The SloanExtension for Galactic Understanding and Exploration 2(SEGUE-2), an expansion of a similar project carried outin SDSS-II (Yanny et al. 2009), used the SDSS spectro-graphs to obtain spectra of about 119,000 stars, mostlyat high Galactic latitudes. The Baryon Oscillation Spec-troscopic Survey (BOSS; Dawson et al. 2013) rebuilt thespectrographs to improve throughput and increase thenumber of fibers to 1000 (Smee et al. 2013). BOSS en-larged the imaging footprint of SDSS to 14,555 deg2, andis obtaining spectra of galaxies and quasars with the pri-mary goal of measuring the oscillation signature in theclustering of matter as a cosmic yardstick to constraincosmological models. The Multi-Object APO Radial Ve-locity Exoplanet Large-area Survey (MARVELS), whichfinished its data-taking in 2012, used a 60-fiber interfero-metric spectrograph to measure high-precision radial ve-locities of stars in a search for planets and brown dwarfs.Finally, the Apache Point Observatory Galactic Evolu-tion Experiment (APOGEE) uses a 300-fiber spectro-graph to observe bright (H < 13.8 mag) stars in the Hband at high resolution (R 22,500) for accurate radialvelocities and detailed elemental abundance determina-tions.

We have previously had two public data releases ofdata from SDSS-III. The Eighth Data Release (DR8;Aihara et al. 2011) included all data from the SEGUE-2survey, as well as 2500 deg2 of new imaging data inthe Southern Galactic Cap as part of BOSS. The NinthData Release (DR9, Ahn et al. 2012) included the firstspectroscopic data from the BOSS survey: over 800,000spectra selected from 3275 deg2 of sky.

This paper describes the Tenth Data Release (here-after DR10) of the SDSS survey. This release includes al-most 680,000 new BOSS spectra, covering an additional3100 deg2 of sky. It also includes the first public re-lease of APOGEE spectra, with almost 180,000 spectraof more than 57,000 stars in a wide range of Galactic en-vironments. As in previous SDSS data releases, DR10 iscumulative; it includes all data that were part of DR19.All data released with DR10 are publicly available on theSDSS-III website96 and links from it.

Science, Beijing, 100012, China.96 http://www.sdss3.org/dr10/

4

The scope of the data release is described in detail inSection 2. We describe the APOGEE data in Section 3,and the new BOSS data in Section 4. The mechanismsfor data access are described in Section 5. We outlinethe future of SDSS in Section 6.

2. SCOPE OF DR10

DR10 presents the release of the first year of datafrom the SDSS-III APOGEE infrared spectroscopic sur-vey and the first 2.5 years of data from the SDSS-IIIBOSS optical spectroscopic survey. In each case thesedata extend to the 2012 telescope shutdown for the sum-mer monsoon season.

APOGEE was commissioned from 2011 May upthrough the summer shutdown in 2011 July. Survey-quality observations began 2011 Aug 31 (UTC-7), cor-responding to Modified Julian Date (MJD) 55804. TheAPOGEE data presented in DR10 include all commis-sioning and survey data taken up to and including MJD56121 (2012 July 13). However, detailed stellar parame-ters are only presented for APOGEE spectra obtained af-ter commissioning was complete. The BOSS data includeall data taken up to and including MJD 56107 (2012 June29).

DR10 also includes the imaging and spectroscopic datafrom SDSS-I/II and SDSS-III SEGUE-2, the imagingdata for the BOSS Southern Galactic Cap first presentedin DR8, as well as the spectroscopy from the first 2.5years of BOSS. Table 1 lists the contents of the datarelease, including the imaging coverage and number ofAPOGEE and BOSS plates and spectra. APOGEEplates are observed multiple times (visits) to buildsignal-to-noise ratio (S/N) and to search for radial ve-locity variations; thus the number of spectra in DR10 issignificantly larger than the number of unique stars ob-served. While there are fewer repeat spectra in BOSS,we sill distinguish between the total number of spectra,and the number of unique objects observed in BOSS aswell. The numbers for the imaging data, unchanged sinceDR8, also distinguish between unique and total area andnumber of detected objects. The multiple repeat obser-vations of the Equatorial Stripe in the Fall sky (Anniset al. 2011), used to search for Type Ia supernovae (Frie-man et al. 2008), dominate the difference between totaland unique area imaged.

New in DR10 are morphological classifications of SDSSimages of galaxies by 200,000 citizen scientists via theGalaxy Zoo project (Lintott et al. 2008, 2011; Willettet al. 2013). These classifications include both the basic(spiralearly-type) morphologies for all 1 million galax-ies from the SDSS-I/II Main Galaxy Sample (Strausset al. 2002), as well as more detailed classifications ofthe internal structures in the brightest 250,000 galaxies.

The celestial footprint of the APOGEE spectroscopiccoverage in DR10 is shown in Figure 1 in Galactic coor-dinates; Figure 2 repeats this in Equatorial coordinates,and shows the imaging and BOSS spectroscopy sky cov-erage as well. The distribution on the sky of SDSS-I/IIand SEGUE-2 spectroscopy is not shown here; see theDR7 and DR8 papers. APOGEE fields span all of theGalactic components visible from APO, including theGalactic center and disk, as well as fields at high Galacticlatitudes to probe the halo. The Galactic center obser-vations occur at high airmass, thus the differential atmo-

spheric refraction across the field of view changes rapidlywith hour angle. Therefore targets in these fields are notdistributed over the full 7 deg2 of each plate, but ratherover a smaller region from 0.8 to 3.1 deg2, as indicatedby the smaller dots in Figure 1. The clump of pointscentered roughly at l = 75, b = +15 are special platestargeting stars previously observed by NASAs Keplermission, as described in detail in Section 3.4.

The additional BOSS spectroscopy fills in most of thedoughnut defined by the DR9 coverage in the NorthGalactic Cap. The DR10 BOSS sky coverage relative tothe 10,000 deg2 full survey region is described further inSection 4.

3. THE APACHE POINT OBSERVATORY GALAXYEVOLUTION EXPERIMENT (APOGEE)

3.1. Overview of APOGEE

Stellar spectra of red giants in theH band (1.51.8 m)show a rich range of absorption lines from a wide varietyof elements. At these wavelengths, the absorption dueto dust in the plane of the Milky Way is much reducedcompared to that in the optical bands. A high-resolutionstudy of stars in the H band allows studies of all com-ponents of the Milky Way, across the disk, in the bulge,and out to the halo.

APOGEEs goal is to trace the history of star forma-tion in, and the assembly of, the Milky Way by obtain-ing H-band spectra of 100,000 red giant candidate starsthroughout the Galaxy. Using an infrared multi-objectspectrograph with a resolution of R / 22,500,APOGEE can survey the halo, disk, and bulge in amuch more uniform fashion than previous surveys. TheAPOGEE spectrograph features a 50.8 cm 30.5 cmmosaiced volume-phase holographic (VPH) grating anda six-element camera having lenses with a maximum di-ameter of 40 cm. APOGEE takes advantage of the fiberinfrastructure on the SDSS telescope, using 300 fibers,each subtending 2 on the sky, distributed over the full7 deg2 field of view (with the exception of plates observedat high airmass, as noted above). The spectrograph it-self sits in a temperature-controlled room, and thus doesnot move with the telescope. The light from the fibersfalls onto three HAWAII-2RG 2K 2K infrared detec-tors (Garnett et al. 2004; Rieke 2007), that cover thewavelength range from 1.514 m to 1.696 m, with twogaps (see Section 3.2 for details). APOGEE targets arechosen with magnitude and color cuts from photometryof the Two-Micron All-Sky Survey (2MASS; Skrutskieet al. 2006), with a median H = 10.9 mag and with99.6% of the stars brighter than H = 13.8 mag (on the2MASS Vega-based system).

The high resolution of the spectra and the stabilityof the instrument allow accurate radial velocities with atypical uncertainty of 100 m s1, and detailed abundancedeterminations for approximately 15 chemical elements.In addition to being key in identifying binary star sys-tems, the radial velocity data are being used to explorethe kinematical structure of the Milky Way and its sub-structures (e.g., Nidever et al. 2012) and to constraindynamical models of its disk (e.g., Bovy et al. 2012).The chemical abundance data allow studies of the chem-ical evolution of the Galaxy (Garca Perez et al. 2013)and the history of star formation. The combination ofkinematical and chemical data will allow important new

SDSS DR10 5

Figure 1. The distribution on the sky of all APOGEE DR10 pointings in Galactic coordinates: the Galactic Center is in the middle of thediagram. Each circle represents a pointing. APOGEE often has several distinct plates for a single location on the sky; DR10 includes 170locations, which are shown above. Smaller circles (primarily near the Galactic Center) represent locations where plates were drilled overonly a fraction of the 7 deg2 focal plane to minimize differential atmospheric refraction. Note the concentration of fields along the GalacticPlane. The concentration of pointings at l = 75, b = +15 is a special program targeting stars observed by the Kepler telescope; seeSection 3.4. (top) Distribution of pointings in both the commissioning and survey phases (both are included in DR10). (bottom) Pointingsdistinguished by the number of visits obtained by DR10 in the survey phase.

constraints on the formation history of the Milky Way.A full overview of the APOGEE survey will be pre-

sented in S. Majewski et al. (2014, in preparation).The APOGEE instrument will be detailed in J. Wil-son et al. (2014, in preparation) and is summarizedhere in Section 3.2. The target selection process forAPOGEE is described in Zasowski et al. (2013) and ispresented in brief here in Section 3.3. In Section 3.4we describe a unique cross-targeting program betweenSDSS-III APOGEE and asteroseismology measurementsfrom the NASA Kepler telescope97 (Gilliland et al. 2010).Section 3.5 describes the reduction pipeline that pro-

97 http://kepler.nasa.gov/

cesses the APOGEE data and produces calibrated one-dimensional spectra of each star, including accurate ra-dial velocities (D. Nidever et al., 2014, in preparation).Important caveats regarding APOGEE data of which po-tential users should be aware are described in Section 3.6.Section 3.7 describes the pipeline that measures stellarproperties and elemental abundances the APOGEEStellar Parameters and Chemical Abundances Pipeline(ASPCAP; M. Shetrone et al., 2014, in preparation;A. Garca-Perez et al., 2014, in preparation, Meszaroset al. 2013). Section 3.8 summarizes the APOGEE dataproducts available in DR10.

3.2. The APOGEE Instrument and Observations

6

Figure 2. The distribution on the sky of all SDSS imaging (top; 14,555 deg2 same as DR8 and DR9) and BOSS and APOGEE DR10spectroscopy (bottom; 6373.2 deg2) in J2000 equatorial coordinates ( = 0 is right of center in this projection). Grey shows regionsincluded in DR9; the increment included in DR10 is in red. The blue shows the positions of APOGEE pointings included in DR10. TheGalactic Plane is shown by the dotted line. The Northern Galactic Cap is on the left of the figure, and the Southern Galactic Cap on theright. The BOSS sky coverage shown is actually constructed using a random subsample of the BOSS DR10Q quasar catalog (Paris et al.2013). The sky below < 30 is never at an airmass of of less than 2.0 from APO (latitude=+324649).

The APOGEE spectrograph measures 300 spectra ina single observation: roughly 230 science targets, 35 onblank areas of sky to measure sky emission, and 35 hot,blue stars to calibrate atmospheric absorption. Thismultiplexing is accomplished using the same aluminumplates and fiber optic technology as have been used forthe optical spectrograph surveys of SDSS. Each plate cor-responds to a specific patch of sky, and is pre-drilled withholes corresponding to the sky positions of objects in thatarea, meaning that each area requires one or more uniqueplates.

The APOGEE spectrograph uses three detectors to

cover the H-band range, blue: 1.5141.581 m,green: 1.5851.644 m, and red: 1.6471.696 m.There are two gaps, each a few nm wide, in wavelengthin the spectra. The spectral line spread function spans1.63.2 pixels per spectral resolution element FWHM, in-creasing from blue to red across the detectors. Thus mostof the blue detector is under-sampled. Figure 3 shows theresults of a typical exposure. Each observation consists ofat least one AB pair of exposures for a given pointingon the sky, with the detector array mechanically offsetby 0.5 pixels along the dispersion direction between thetwo exposures. This well-controlled sub-pixel dithering

SDSS DR10 7

Figure 3. (top) A 2D spectrogram from the APOGEE instrument. The three chips (blue, green, and red) are shown with wavelengthincreasing to the right across the full APOGEE wavelength range of 1.5141.696 m. The gaps between the chips are slightly larger thanas displayed in this image. Each fiber is imaged onto several pixels (vertically). Note the vertical series of points from sky lines in eachfiber, and the horizontal spectra of faint stars and sky fibers. (bottom) Expanded view of the central 18 fibers and central 6 nm of eachchip.

allows the derivation of combined spectra with approx-imately twice the sampling of the individual exposures.Thus the combined spectra are properly sampled, includ-ing all wavelengths from the blue detector. The actualline spread function as a function of wavelength is pro-vided as a Gauss-Hermite function for each APOGEEspectrum in DR10.

A typical observation strategy is two ABBA se-quences. Each sequence consists of four 500-second ex-posures to reach the target S/N for a given observation.The combination of all AB or BA pairs for a givenplate during a night is called a visit. The visit is thebasic product for what are considered individual spectrafor APOGEE (although the spectra from the individualexposures are also made available). While the total expo-sure time for a visit is 4,000 seconds (24500 seconds),due to the varying lengths of night and other schedulingissues, we often gathered more or less than the stan-dard two ABBA sequences on a given plate in a night.APOGEE stars are observed over multiple visits (thegoal is at least three visits) to achieve the planned S/N.Figure 4 shows the distribution of the number of visits forstars included in DR10; presently, most stars have threeor fewer visits, but this distribution will broaden withthe final data release. These visits are separated acrossdifferent nights and often different seasons, allowing usto look for radial velocity variability due to binarity on avariety of timescales. The distribution of time intervalsbetween visits is shown in Figure 5, with peaks at oneand two lunations (30 and 60 days).

Each visit is uniquely identified by the plate num-ber and MJD of the observation. Plates aregenerally re-plugged between observations, so whileplate+MJD+fiber remains a unique identifier inAPOGEE spectra as it is in optical SDSS spectra,plate+fiber does not refer to the same object acrossall visits. The spectra from all visits are co-added toproduce the aggregate spectrum of the star. The final

Figure 4. The distribution of number of spectroscopic visits forAPOGEE stars included in DR10. While the bulk of stars havethree or fewer visits, they may have reached our spectral S/N re-quirement if they are bright enough; see Figure 7.

co-added spectra are processed by the stellar parameterspipeline described in Section 3.7.

The aim is for a final co-added spectrum of each starwith a S/N of > 100 per half-resolution element.98 Fig-ures 6 and 7 show the distribution of S/N; not surpris-ingly, S/N is strongly correlated with the brightness ofthe star. The DR10 data include some stars that have yetto receive their full complement of visits and thus havesignificantly lower quality spectra. Future data releaseswill include additional visits for many stars, leading toan increase in total co-added S/N as well as more refinedstellar parameters.

The APOGEE plates are drilled with the same plate-drilling machines used for BOSS, and the plate num-bers are sequential. This scheme means that the BOSSand APOGEE plate numbers are interleaved and that noplate number is assigned to both a BOSS and APOGEEplate.

The quality of the APOGEE commissioning data (thattaken prior to 2011 Aug 31) is lower than the survey data,

98 This is a refinement from the less stringent goal of S/N> 100per full-resolution element given in Eisenstein et al. (2011).

8

Table 1Contents of DR10

Optical Imaginga

Total Uniqueb

Area Imaged [deg2] 31637 14555Cataloged Objects 1231051050 469053874

APOGEE Spectroscopy

Commiss. Survey TotalPlate-Visits 98 586 684Plates 51 232 281Pointings 43 150 170

Spectra StarsAll Starsc 178397 57454Commissioning Stars 24943 11987Survey Stars 153454 47452

Stars with S/N > 100d 47675Stars with 3 visits 29701Stars with 12 visits 923Stellar parameter standards 5178 1065Radial velocity standards 162 16Telluric line standards 24283 7003Ancillary science program objects 8894 3344

BOSS Spectroscopy

Total Uniqueb

Spectroscopic effective area [deg2] 6373.2Platese 1515 1489Optical Spectra observedf 1507954 1391792

All Galaxies 927844 859322CMASSg 612195 565631LOWZg 224172 208933

All Quasars 182009 166300Mainh 159808 147242Main, 2.15 < z < 3.5i 114977 105489

Ancillary program spectra 72184 65494Stars 159327 144968

Standard stars 30514 27003Sky spectra 144503 138491Unclassified spectraj 101550 89003

All Optical Spectroscopy from SDSS up through DR10

Total spectra 3358200Total useful spectrak 3276914

Galaxies 1848851Quasars 316125Stars 736484Sky 247549Unclassifiedj 138663

a These numbers are unchanged since DR8.b Removing all duplicates, overlaps, and repeat visits from the To-tal column.c 2,155 stars were observed both during the commissioning andsurvey phases. The co-added spectra are kept separate betweenthese two phases. Thus the number of coadded spectra is greaterthan the number of unique stars observed.d Signal-to-noise ratio per half resolution element > 100.e Twenty-six plates of the 1515 observed plates were re-plugged andre-observed for calibration purposes. Six of the 1489 unique platesare different drillings of the same set of objects.f This excludes the small fraction of the observations through fibersthat are broken or that fell out of their holes after plugging. Therewere 1,515,000 spectra attempted.g CMASS and LOWZ refer to the two galaxy target categoriesused in BOSS (Ahn et al. 2012). They are both color-selected, withLOWZ galaxies in the redshift range 0.15 < z < 0.4, and CMASSgalaxies in the range 0.4 < z < 0.8.h This counts only quasars that were targeted by the main quasarsurvey (Ross et al. 2012), and thus does not include those fromancillary programs (Dawson et al. 2013).i Quasars with redshifts in the range 2.15 < z < 3.5 provide themost signal in the BOSS spectra of the Ly- forest.j Non-sky spectra for which the automated redshift/classificationpipeline (Bolton et al. 2012) gave no reliable classification, as indi-cated by the ZWARNING flag.k Spectra on good or marginal plates.

Figure 5. The distribution of time between visits for APOGEEstars, useful for determining the sensitivity to radial velocity vari-ations due to binarity. This quantity is the absolute value of thetime difference for all unique pairs of visits for each star. The mostprominent peaks are at one and two months.

Figure 6. Reported S/N per pixel of APOGEE DR10 co-addedstellar spectra. Repeated observations imply that there is a prac-tical limit of S/N 200 in the co-added spectra, shown as thedot-dashed line. The dashed line denotes the goal of S/N 100per half-resolution element, corresponding to S/N 80 per pixelin the co-added spectra.

6 8 10 12 14 16H (2MASS)

100

101

102

103

Sig

nal-

to-N

ois

e R

ati

o

0.000.250.500.751.001.251.501.752.00

log 1

0(#

sta

rs/b

in)

Figure 7. S/N per pixel of spectra of stars as a function of theirapparent H-band magnitude (density is on a log scale). The verti-cal dot-dashed lines indicate the magnitude limits for stars at eachvalue of the final number of visits: 1, 3, 6, 12, 24 visits for H = 11.0,12.2, 12.8, 13.3, and 13.8 mag. The horizontal dashed line denotesthe target S/N 100 per half-resolution element, correspondingto S/N 80 per pixel in the co-added spectra.

due to optical distortions and focus issues that were re-solved before the official survey was started. The biggestdifference lies in the red chip, which has significantlyworse spectral resolution in the commissioning data thanin the survey data. Because of this degradation, the datawere not under-sampled, and spectral dithering was notdone during commissioning.

Many of the targets observed in commissioning wereselected in the same way as those observed during thesurvey (Section 3.3), though several test plates were de-signed with different criteria to test the selection algo-rithms (e.g., without a color limit or with large numbersof potential telluric calibration stars). Total exposure

SDSS DR10 9

times for the commissioning plates were similar to thoseof the survey plates. Because the spectral resolution ofcommissioning data is worse, it cannot be analyzed usingASPCAP with the same spectral libraries with which thesurvey data are analyzed. As a result, DR10 does not re-lease any stellar parameters other than radial velocitiesfor commissioning data; subsequent releases may includestellar parameters for APOGEE commissioning derivedusing appropriately matched libraries and/or with onlya subset of the spectral range.

3.3. APOGEE Main and Ancillary Targets

APOGEE main targets are selected from 2MASS data(Skrutskie et al. 2006) using apparent magnitude lim-its to meet the S/N goals and a dereddened color cut of(JKs)0 > 0.5 mag to select red giants in multiple com-ponents of the Galaxy: the disk, bulge, and halo. Thisselection results in a sample of objects that are predom-inantly red giant stars with 3500 < Teff < 5200 K andlog g < 3.5 (where g is in cm s2 and the logarithm isbase 10). Fields receiving three visits have a magnitudelimit of H = 12.2; the deepest plates with 24 visits go toH = 13.8.

APOGEE has also implemented a number of ancillaryprograms to pursue specific investigations enabled by itsunique instrument. The selection of the main target sam-ple and the ancillary programs, together with the bitflags that can be used to identify why an object was tar-geted for spectroscopy, are described in detail in Zasowskiet al. (2013). In DR10, APOGEE stars are named basedon a slightly shortened version of their 2MASS ID (e.g.,2M21504373+4215257 is stored for the formal designa-tion 2MASS 21504373+4215257). A few objects thatdont have 2MASS IDs are designated as AP, followedby their coordinates.

APOGEE targets were chosen in a series of fields de-signed to sample a wide range of Galactic environments(Figure 1): in the halo predominantly at high latitudes,in the disk, in the central part of the Milky Way (limitedin declination), as well as special targeted fields over-lapping the Kepler survey (Section 3.4), and a variety ofopen and globular clusters with well-characterized metal-licity in the literature.

The effects of Galactic extinction on 2MASS photome-try can be quite significant at low Galactic latitude. Wecorrect for this using the Spitzer IRAC GLIMPSE sur-vey (Benjamin et al. 2003; Churchwell et al. 2009) andthe Wide-field Infrared Survey Explorer (WISE; Wrightet al. 2010) = 4.5 m data following the Rayleigh-Jeans Color Excess Method described in Majewski et al.(2011) and Zasowski et al. (2013) using the color extinc-tion curve from Indebetouw et al. (2005). Figure 8 showsthe measured and reddening-corrected JHKs color-colorand magnitude-color diagrams for the APOGEE stars in-cluded in DR10.

In regions of high interstellar extinction, even intrinsi-cally blue main sequence stars can be reddened enough tooverlap the nominal red giant locus. Dereddening theseapparent colors allows us to remove these dwarfs withhigh efficiency from the final targeted sample. However,G and K dwarfs cannot be distinguished from red giantson the basis of their dereddened broadband colors, withthe result that a fraction of the APOGEE sample is com-posed of such dwarfs. In the disk they are expected to

(JH) 2MASS

0

1

2

3

4

(HKs)

2M

ASS

(JH)0

(HKs) 0

0 1 2 3 4(JKs ) 2MASS

56789

10111213

H (

2M

ASS)

0 1 2 3 4(JKs )0

H0

Figure 8. Two-dimensional histogram of the APOGEE DR10stars in (top) 2MASS JHKs color space; and (bottom) 2MASS Hvs. JKs. The left column shows observed magnitudes and colorsfrom 2MASS, while the right column has been dereddened based onH 4.5 m color as in Zasowski et al. (2013). The vertical dashedline at (J Ks)0 = 0.5 shows the selection of the main APOGEEred giant sample; bluer objects include telluric calibration stars,data taken during commissioning, and ancillary program targets.The grey scale is logarithmic in number of stars.

comprise less than 20% of the sample, and this appears tobe validated by our analysis of the spectra. Disk dwarfsare expected to be a larger contaminant in halo fields, soin many of these, target selection was supplemented byWashington and intermediate-band DDO51 photometry(Canterna 1976; Clark & McClure 1979; Majewski et al.2000) using the 1.3-m telescope of the U.S. Naval Obser-vatory, Flagstaff Station. Combining this with 2MASSphotometry allows us to distinguish dwarfs and giants(see Zasowski et al. 2013 for details).

Exceptions to the (JKs)0 > 0.5 mag color limit thatappear in DR10 include the telluric calibration stars,early-type stars targeted in well-studied open clusters,stars observed on commissioning plates that did not em-ploy the color limit, and stars in sparsely populated halofields where a bluer color limit of (J Ks)0 > 0.3 magwas employed to ensure that all fibers were utilized. An-cillary program targets may also have colors and magni-tudes beyond the limits of APOGEEs normal red giantsample.

3.4. APOKASC

Non-radial oscillations are detected in virtually all redgiants targeted by the Kepler mission (Borucki et al.2010; Hekker et al. 2011), and the observed frequenciesare sensitive diagnostics of basic stellar properties such asmass, radius, and age (for a review, see Chaplin & Miglio2013). Abundances and surface gravities measured fromhigh-resolution spectroscopy of these same stars are animportant test of stellar evolution models, and allow ob-servational degeneracies to be broken.

With this in mind, the APOKASC collaboration wasformed between SDSS-III and the Kepler Asteroseismol-ogy Science Collaboration (KASC) to analyze APOGEEspectra for 10, 000 stars in fields observed by the Ke-pler telescope (see Figure 1). The joint measurement

10

of masses, radii, ages, evolutionary states, and chemicalabundances for all these stars will enable significantly en-hanced investigations of Galactic stellar populations andfundamental stellar physics.

DR10 presents 4,204 spectra of 2,308 stars of the an-ticipated final APOKASC sample. Asteroseismic datafrom the APOKASC collaboration were used to calibratethe APOGEE spectroscopic surface gravity results forall APOGEE stars presented in DR10 (Meszaros et al.2013). A joint asteroseismic and spectroscopic value-added catalog will be released separately (M. Pinson-neault et al., 2014, in preparation).

3.5. APOGEE Data Analysis

The processing of the two-dimensional spectrogramsand extraction of one-dimensional co-added spectra willbe fully described in D. Nidever et al. (2014, in prepa-ration). We provide here a brief summary to help thereader understand how individual APOGEE exposuresare processed. A 500-second APOGEE exposure actu-ally consists of a series of non-destructive readouts ev-ery 10.7 seconds that result in a three-dimensional datacube. The first step in processing is to extract a two-dimensional image from a combination of these mea-surements. After dark current subtraction, the up-the-ramp values for each pixel are fit to a line to derivethe count rate for that pixel. Cosmic rays create char-acteristic jumps in the up-the-ramp signal that areeasily recognized, removed, and flagged for future ref-erence. The count rate in each pixel is multiplied bythe exposure time to obtain a two-dimensional image.These two-dimensional images are then dark-subtractedand flat-fielded. One-dimensional spectra are extractedsimultaneously for the entire set of 300 fibers based onwavelength and profile fits from flat-field calibration im-ages. Both the flat-field response and spectral tracesare very stable due to the controlled environment ofthe APOGEE instrument, which has been under vac-uum and at a uniform temperature continuously since itwas commissioned. Wavelength calibration is performedusing emission lines from thorium-argon and uranium-neon hollow cathode lamps. The wavelength solution isthen adjusted from the reference lamp calibration on anexposure-to-exposure basis using the location of the nightsky lines.

The individual exposure spectra are then corrected fortelluric absorption and sky emission using the sky spec-tra and telluric calibration star spectra, and combinedaccounting for the dither offset between each A andB exposure. This combined visit spectrum is flux-calibrated based on a model of the APOGEE instru-ments response from observations of a blackbody source.The spectrum is then scaled to match the 2MASS mea-sured apparent H-band magnitude. A preliminary radialvelocity is measured after matching the visit spectrum toone from a pre-computed grid of synthetic stellar spectra,and is stored with the individual visit spectrum.

In addition to the individual visit spectra, theAPOGEE software pipeline coadds the spectra from dif-ferent visits to the same field, yielding a higher S/N spec-trum of each object. Figure 9 shows examples of highS/N co-added flux-calibrated spectra from APOGEE forstars with a range of Teff and with a range of [M/H]. A fi-nal and precise determination of the relative radial veloc-

ities on each visit is determined from cross-correlation ofeach visit spectrum with the combined spectrum; the ve-locities are put on an absolute scale by cross-correlatingthe combined spectrum with the best-matching spectrumin a pre-computed synthetic grid. The combined spectraare output on a rest-wavelength scale with logarithmi-cally spaced pixels with approximately three pixels perspectral resolution element.

3.6. Issues with APOGEE Spectra

Users should be aware of several features and potentialissues with the APOGEE data. This is the first datarelease for APOGEE; the handling of some of these issuesby the pipelines may be improved in subsequent datareleases.

Many of these issues are documented in the data bythe use of bitmasks that flag various conditions. Forthe APOGEE spectral data, there are two bitmasksthat accompany the main data products Each one-dimensional extracted spectrum includes a signal, uncer-tainty, and mask arrays. The mask array is a bitmask,APOGEE PIXMASK99, that flags data-quality conditionsthat affect a given pixel. A non-zero APOGEE PIXMASKvalue for a pixel indicates a potential data-quality con-cern that affects that pixel. Each stellar-parametersanalysis of each star is accompanied by a single bit-mask, APOGEE STARFLAG100, that flags conditions at thefull spectrum level.

The most important data-quality features to be awareof include:

Gaps in the spectra: There are gaps in the spectracorresponding to the regions that fall between the threedetectors. There are additional gaps due to bad or hotpixels on the arrays. As multiple dithered exposures arecombined to make a visit spectrum, values from missingregions cannot be used to calculate the dither-combinedsignal in nearby pixels; as a result, these nearby pixelsare set to zero and the BADPIX bit is set for these pix-els in APOGEE PIXMASK. Generally, the bad pixels affectneighboring pixels only at a very low level, and the datain the latter may be usable; in subsequent data releases,we will preserve more of the data, while continuing toidentify potential bad pixels in the pixel mask.

Imperfect night-sky-line subtraction: TheEarths atmosphere has strong and variable emission inOH lines in the APOGEE bandpass. At the locationof these lines, the sky flux is many times brighter thanthe stellar flux for all except the brightest stars. Even ifthe sky subtraction algorithm were perfect, the photonnoise at the positions of these sky lines would dominatethe signal, so there is little useful information at the cor-responding wavelengths. The spectra in these regionscan show significant sky line residuals. These regions aremasked for the stellar parameter analysis so that theydo not impact the results. The affected pixels have theSIG SKYLINE bit set in APOGEE PIXMASK.

Error arrays do not track correlated errors:APOGEE spectra from an individual visit are made bycombining multiple individual exposures taken at differ-ent dither positions. Because the dithers are not spacedby exactly 0.5 pixels, there is some correlation between

99 http://www.sdss3.org/dr10/algorithms/bitmask apogee pixmask.php100 http://www.sdss3.org/dr10/algorithms/bitmask apogee starflag.php

SDSS DR10 11

pixels that is introduced when combined spectra are pro-duced. The error arrays for the visit spectra do not in-clude information about these correlations. In the visitspectra, these correlations are generally small becausethe dither mechanism is generally quite accurate. How-ever, when multiple visit spectra are combined to makethe final combined spectra, they must be re-sampled ontoa common wavelength grid, taking into account the dif-ferent observer-frame velocities of each individual visit.This re-sampling introduces significant additional corre-lated errors between adjacent pixels that are also nottracked in the error arrays.

Error arrays do not include systematic errorfloors: The errors that are reported for each spectrumare derived based on propagation of Poisson and read-out noise. However, based on observations of bright hotstars, we believe that other, possibly systematic, uncer-tainties currently limit APOGEE observations to a maxi-mum S/N per half resolution element of 200. The errorarrays published in DR10 currently report the estimatederrors without any contribution from a systematic com-ponent. However, for the ASPCAP analysis, we imposean error floor corresponding to 0.5% of the continuumlevel.

Fiber crosstalk: While an effort is made not toput faint stars adjacent to bright ones on the detec-tor to avoid excessive spillage of light from one to theother, this occasionally occurs. We flag objects (inAPOGEE STARFLAG) with a BRIGHT NEIGHBOR flag if an ad-jacent star is > 10 times brighter than the object, andwith a VERY BRIGHT NEIGHBOR flag if an adjacent star is> 100 times brighter; in the latter case, the individualspectra are marked as bad and are not used in combinedspectra.

Persistence in the blue chip: There is a knownsuperpersistence in 1/3 of the region of the blueAPOGEE data array, and to a lesser extent in some re-gions of the green chip, whereby some of the chargefrom previous exposures persists in subsequent expo-sures. Thus the values read out in these locations de-pend on the previous exposure history for that chip.The effect of superpersistence can vary significantly,but residual signal can amount to as much as 1020% of the signal from previous exposures. The cur-rent pipeline does not attempt to correct for this ef-fect; any such correction is likely to be rather com-plex. For the current release, pixels known to be af-fected by persistence are flagged in APOGEE PIXMASK atthree different levels (PERSIST LOW, PERSIST MEDIUM,PERSIST HIGH). Spectra that have significant numbers ofpixels (> 20% of total pixels) that fall in the persistenceregion have comparable bits set in the APOGEE STARFLAGbitmask to warn that the spectra for these objects may becontaminated. In a few cases, the effect of persistence isseen dramatically as an elevated number of counts in theblue chip relative to the other arrays; these are flagged asPERSIST JUMP POS in APOGEE STARFLAG. We are still ac-tively investigating the effect of persistence on APOGEEspectra and derived stellar parameters, and are workingon corrections that we intend to implement for futuredata releases.

3.7. APOGEE Stellar Parameter and ChemicalAbundances Pipeline (ASPCAP)

The ultimate goal of APOGEE is to determine theeffective temperature, surface gravity, overall metallic-ity, and detailed chemical abundances for a large sam-ple of stars in the Milky Way. Stellar parameters andchemical abundances are extracted from the continuum-normalized co-added APOGEE spectra by comparingwith synthetic spectra calculated using state-of-the-artmodel photospheres (Meszaros et al. 2012) and atomicand molecular line opacities (Shetrone et al., in prepara-tion).

Analysis of high-resolution spectra is traditionally doneby hand. However, given the sheer size of APOGEEsspectral database, automatic analysis methods must beimplemented. For that purpose, ASPCAP searches forthe best fitting spectrum through 2 minimization withina pre-computed multi-dimensional grid of synthetic spec-tra, allowing for interpolation within the grid. The out-put parameters of the analysis are effective temperature(Teff), surface gravity (log g), metallicity ([M/H]), andthe relative abundances of elements ([/M])101, carbon([C/M]), and nitrogen ([N/M]). The micro-turbulencequoted in the DR10 results is not an independent quan-tity, but is instead calculated directly from the value oflog g. Figure 10 shows an example ASPCAP fit to anAPOGEE spectrum of a typical star. ASPCAP will befully described in an upcoming paper (A. Garca Perezet al., 2014, in preparation).

Chemical composition parameters are defined as fol-lows. The abundance of a given element X is definedrelative to solar values in the standard way:

[X/H] = log10(nX/nH)star log10(nX/nH) , (1)where nX and nH are respectively the numbers of atomsof element X and hydrogen, per unit volume, in the stel-lar photosphere. The parameter [M/H] is defined as anoverall metallicity scaling, assuming the solar abundancepattern. The deviation of the abundance of element Xfrom that pattern is given by

[X/M] = [X/H] [M/H] . (2)The elements considered in the APOGEE spectral li-braries are O, Ne, Mg, Si, S, Ca, and Ti, and [/H] isdefined as an overall scaling of the abundances of thoseelements, where they are assumed to vary together whilekeeping their relative abundances fixed at solar ratios.For DR10, we allow four chemical composition parame-ters to vary: the overall metallicity, and the abundancesof elements, carbon, and nitrogen. Carbon, nitro-gen, and oxygen contribute significantly to the opacityin APOGEE spectra of cool giants, particularly in theform of molecular lines due to OH, CO, and CN.

3.7.1. Parameter Accuracies

Meszaros et al. (2013) have compared the outputs ofASPCAP to stellar parameters in the literature for starstargeted by APOGEE in open and globular clusters span-ning a wide range in metallicity. These comparisons un-covered small systematic differences between ASPCAP

101 The relative -element abundance is labeled ALPHAFE in theDR10 tables and files, but it is more accurately the ratio of the elements to the overall metallicity, [/M].

12

and literature results, which are mostly based on high-resolution optical spectroscopy. These differences are notentirely understood yet, and we hope they will be cor-rected in future data releases. In the meantime, calibra-tions have been derived to bring APOGEE and literaturevalues into agreement. With these offsets in place, theAPOGEE metallicities are accurate to within 0.1 dex forstars of S/N > 100 per half-resolution element that liewithin a strict range of Teff , log g, and [M/H]. Basedon observed scatter in the ASPCAP calibration clusters,we estimate that the internal precision of the APOGEEmeasurements is 0.2 dex for log g, 150 K for Teff , and0.1 dex for [/M] (see Meszaros et al. 2013, for details).

Because most of the observed cluster stars are giants,the applied calibration offsets only apply to giants. Theparameters of dwarfs are generally accurate enough todetermine that they are indeed higher surface gravitystars, but otherwise their parameters are likely to bemore uncertain: one reason for this is that rotation islikely to be important for a larger fraction of these stars,and the effects of rotation are not currently included inour model spectral libraries.

APOGEE mean values per cluster of [/M] are ingood agreement with those in the literature. How-ever, there are systematic correlations between [/M]and both [M/H] and Teff for stars outside the range0.5 [M/H] 0.1. Moreover, important systematiceffects may be present in [/M] for stars cooler thanTeff 4200 K. We therefore discourage use of [/M]for stars with Teff < 4200 K or with [M/H]< 0.5 or[M/H]> +0.1.

Figure 15 in Meszaros et al. (2013) shows the root-mean square scatter in [/M] for red giants in open andglobular clusters, as a measure of the uncertainty in thisparameter. However, given the trends in [/M] withother stellar parameters, care should be taken when es-timating the accuracy of [/M].

Comparison with literature values for carbon and ni-trogen abundances shows large scatter and significantsystematic differences. In view of the relative paucityand uncertainty of literature data for these elements,more work is needed to understand these systematic andrandom differences before APOGEE abundances for car-bon and nitrogen can be confidently adopted in scienceapplications.

3.7.2. ASPCAP Outputs

In DR10, we provide calibrated values of effective tem-perature, surface gravity, overall metallicity, and [/M]for giants. In addition, we provide the raw ASPCAPresults (uncalibrated, and thus, to some extent, unval-idated) for all six parameters for all stars with survey-quality data. Since commissioning data have lower res-olution, different spectral libraries are needed to derivestellar parameters from them, and therefore ASPCAPresults are not provided for these spectra at this time.For all stars with ASPCAP results, we also provide in-formation about the quality of the fit (2) and severalbitmasks (APOGEE ASPCAPFLAG and APOGEE PARAMFLAG)that flag several conditions that may cause the results tobe less reliable. Among these conditions are abnormallyhigh 2 in the fit, best-fit parameters near the edges ofthe searched range, evidence in the spectrum of signifi-cant stellar rotation, and so on. Users should check the

values of these bitmasks before using the ASPCAP pa-rameters.

Figure 11 shows the distribution of stellar propertiesderived by ASPCAP for stars included in DR10. TheASPCAP spectral libraries are currently only calibratedin the range 3610 < Teff < 5255 K. Thus the reliableASPCAP Teff reported values lie only in this range, witha peak at about 4800 K. The surface gravity distribu-tion peaks at log g 2.5, corresponding to red clumpstars, and is strongly correlated with surface tempera-ture. The ASPCAP models are calibrated in the range0.5 < log g < 3.6, which is reflected in the range shown.Because of the strong concentration of targeted fields tothe Galactic plane (Figure 1), the metallicity distributionpeaks just below solar levels, with a tail extending from[M/H] 0.5 to below 2.3. The [/M] abundance dis-tribution has both -rich and -poor stars, which reflectsthe variety of populations explored by APOGEE.

Figure 12 shows the excellent agreement of the ASP-CAP log g, Teff , and [M/H] values with the isochronemodels of Bressan et al. (2012).

3.8. APOGEE Data Products

The APOGEE data as presented in DR10 are avail-able as the individual 500-second spectra taken on aper-exposure basis (organized both by object and byplate+MJD+fiber), as combined co-added spectra ona per-object basis, and as continuum-normalized spec-tra used by the APOGEE pipeline (ASPCAP) whenit computes stellar properties (Section 3.7). The indi-vidual raw exposure files, processed spectra, and com-bined summary files of stellar parameters are provided asFITS102 files (Wells et al. 1981) through the DR10 Sci-ence Archive Server (SAS). The DR10 Catalog ArchiveServer (CAS) provides the basic stellar parameters (in-cluding the radial velocity) from the APOGEE spectraon a per-visit (SQL table apogeeVisit) and a co-addedstar basis (SQL table apogeeStar). The ASPCAP re-sults are provided in the SQL table aspcapStar; the co-variances between these parameters are given in a sepa-rate table, aspcapStarCovar.

To allow one to recreate the sample selection, all ofthe parameters used in selecting APOGEE targets areprovided in DR10 in the SQL table apogeeObject.

Example queries for APOGEE data using the CAS areprovided as part of the DR10 web documentation103.

4. THE BARYON OSCILLATION SPECTROSCOPICSURVEY (BOSS)

An overview of the BOSS survey is presented in detailin Dawson et al. (2013), and the instrument is describedin Smee et al. (2013). BOSS is obtaining spectra of 1.5million galaxies (Ahn et al. 2012), and 150,000 quasarswith redshifts between 2.15 and 3.5 (Ross et al. 2012),selected from 10,000 deg2 of SDSS imaging data. Thelarge-scale distribution of galaxies and the structure inthe quasar Lyman forest, allow measurements of thebaryon oscillation signature as a function of redshift (An-derson et al. 2012, 2013; Busca et al. 2013). In addition,about 5% of the fibers are devoted to a series of ancillary

102 http://fits.gsfc.nasa.gov/103 http://www.sdss3.org/dr10/irspec/catalogs.php#examples

SDSS DR10 13

Figure 9. Typical APOGEE spectra at high S/N. (left) Spectra of stars with 5000 K> Teff > 3750 K at constant [M/H]= 0.2 (acharacteristic [M/H] for the sample). The trend in line intensity from top to bottom is driven by decreasing Teff (which is stronglycorrelated with log g see Figure 11). (right) Spectra of stars with 1.4

14

Figure 11. The one-dimensional and two-dimensional distributions of APOGEE stellar parameters temperatures, surface gravities,metallity, and [/M] for all 29,438 APOGEE stars in DR10 which have reliable ASPCAP fits. The [/M] values are only shown for the16,066 star subset with Teff > 4200 K and 0.5 2 quasars that the stan-dard BOSS quasar target selection may have missed, andto explore the properties of quasars selected in the in-frared.

These objects were required to have detections in the3.6 m, 4.5 m, and 12 m bands, and to be pointsources in SDSS imaging. They were selected with thefollowing color cuts:

(u g) > 0.4 and (g r) < 1.3. (3)

The requirement of a 12 m detection removes essentiallyall stellar contamination, without any WISE color cuts.

There are 5,007 spectra from this sample in DR10, witha density of 1.5/deg2 over the 3, 100 deg2 of new area

added by BOSS in DR10. Almost 3000 of these objectsare spectroscopically confirmed to be quasars, with red-shifts up to z = 3.8. Nine-hundred ninety-nine of theseobjects have z > 2.15.

Given the use of WISE photometry in target selec-tion, we have imported the WISE All-Sky Release cat-alog (Cutri et al. 2012) into the SDSS Catalog ArchiveServer (CAS), and performed an astrometric cross-matchwith 4 matching radius with the SDSS catalog objects.We find no systematic shift between the WISE and SDSSastrometric systems; 4 extends well into the tail of thematch distance distribution. The results of this match-ing are also available as individual files in the ScienceArchive Server (SAS).

4.2. Updates to BOSS Data Processing

We have become aware of transient hot columns onthe spectrograph CCDs. Because fiber traces lie approx-

SDSS DR10 15

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Figure 12. ASPCAP log g vs. Teff with the points color-coded by [M/H]. Overplotted are isochrones for a 4 Gyr population of RGB starswith [/Fe]= 0 from Bressan et al. (2012) on the same color-coded metallicity scale. The isochrones are for [M/H] = 1.9,1.0,0.58,and +0.14 from left to right.

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Figure 13. BOSS DR10 spectroscopic sky coverage in the North-ern Galactic Cap (top) and Southern Galactic Cap (bottom).The grey region is the coverage goal for the final survey, totaling10,000 deg2. The color coding indicates the fraction of CMASSgalaxy targets that receive a fiber; the fact that no two fibers canbe placed closer than 62 on a given plate reduces the average com-pleteness to 94%. Note the higher completeness on the Equator inthe Southern Galactic Cap (Stripe 82) where the plates are tiledwith more overlapping area to recover collided galaxies.

0 2.0 4.0 6.0 8.0 10.0 12.0Lookback Time [Gyr]

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Figure 14. The distribution of BOSS DR10 spectroscopic objectsversus lookback time for the 144,968 unique stars; 859,322 uniquegalaxies; and 166,300 unique quasars. Lookback time is based onthe observed redshift under the assumption of a CDM cosmology(Komatsu et al. 2011). This figure is nearly identical to the equiv-alent for DR9 (Figure 3 of Ahn et al. (2012)), scaled by a factor of1.8.

imately along columns, a bad column can adversely af-fect a large swath of a given spectrum. With this inmind, unusual-looking spectra associated with fibers 40,556, and 834 and fibers immediately adjacent shouldbe treated with suspicion; these objects are often erro-neously classified as z > 5 quasars. We will improve themasking of these bad columns in future data releases.

We have identified 2748 objects with spectra whose as-trometry is unreliable in the SDSS imaging due to track-ing or focus problems of the SDSS telescope while scan-ning. As a consequence, the fibers may be somewhatoffset from the true position of the object, often missing

16

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SDSS DR10 17

interfaces are available, each designed to accomplish aspecific task.

Color images of regions of the sky in JPEG format(based on the g, r and i images; see Lupton et al.2004) can be viewed in a web browser with theSkyServer Navigate tool. These are presented athigher resolution, and with greater fidelity, thanin previous releases. With DR10 we also includeJPEG images of the 2MASS data to complementthe APOGEE spectra.

FITS images can be searched for, viewed, anddownloaded through the SAS Webapp.

Complete catalog information (astrometry, pho-tometry, etc.) of any imaging object can be viewedthrough the SkyServer Explore tool.

Individual spectra, both optical and infrared, canbe searched for, viewed, and downloaded throughthe SAS Webapp.

Catalog search tools are available through the Sky-Server interface to the CAS, each of which returnscatalog data for objects that match supplied cri-teria. For more advanced queries, a powerful andflexible catalog search website called CasJobs al-lows users to create their own personalized datasets and then to modify or graph their data.

Links to all of these methods are provided athttp://www.sdss3.org/dr10/data access/.

The DR10 web site also features data access tutorials,a glossary of SDSS terms, and detailed documentationabout algorithms used to process the imaging and spec-troscopic data and select spectroscopic targets.

Imaging and spectroscopic data from all prior data re-leases are also available through DR10 data access tools,with the sole caveat that the 303 imaging runs cover-ing the equatorial stripe in the Fall sky (Stripe 82) areonly fully provided in DR7107 only the good quality im-ages are included from Stripe 82 in DR8 and subsequentreleases.

6. FUTURE

The SDSS-III project will present two more public datareleases: DR11 and DR12, both to be released in De-cember 2014. DR11 will include data taken through thesummer of 2013. DR12 will be the final SDSS-III datarelease and will include the final data through Summer2014 from all observations with APOGEE, BOSS, MAR-VELS, and SEGUE-2.

In 2014 July, operation of the 2.5-m Sloan FoundationTelescope will be taken over by the next generation ofSDSS, currently known as SDSS-IV, which plans to op-erate for six years. SDSS-IV consists of three surveysmapping the Milky Way Galaxy, the nearby galaxy pop-ulation, and the distant universe. APOGEE-2 will con-tinue the current APOGEE program of targeting MilkyWay stars to study Galactic archaeology and stellar as-trophysics. It will include a southern component, ob-serving from the 2.5-m du Pont Telescope at Las Cam-panas Observatory, Chile, allowing a full-sky view of the

107 http://skyserver.sdss.org/dr7

structure of the Milky Way. Mapping Nearby Galaxiesat APO (MaNGA) will use the BOSS spectrograph in anew mode, bundling fibers into integral field units to ob-serve 10,000 nearby galaxies with spatially resolved spec-troscopy. MaNGA has already observed a small numberof targets using BOSS time to test its planned hardwareconfiguration. Finally, the Extended Baryon OscillationSpectroscopic Survey (eBOSS) will create the largest vol-ume three-dimensional map of the universe to date, tomeasure baryon acoustic oscillations and constrain cos-mological parameters in the critical and largely unex-plored redshift range 0.6 < z < 2.1. eBOSS will also ob-tain spectra of X-ray sources detected by the eROSITAsatellite (Predehl et al. 2010), as well as of variable starsand quasars to understand their physical nature. TheSDSS-IV collaboration will continue the production anddistribution of cutting-edge and diverse data sets throughthe end of the decade.

SDSS-III Data Release 10 makes use of data prod-ucts from the Two Micron All Sky Survey, which is ajoint project of the University of Massachusetts and theInfrared Processing and Analysis Center/California In-stitute of Technology, funded by the National Aeronau-tics and Space Administration and the National ScienceFoundation.

SDSS-III Data Release 10 makes use of data productsfrom the Wide-field Infrared Survey Explorer, which is ajoint project of the University of California, Los Angeles,and the Jet Propulsion Laboratory/California Instituteof Technology, funded by the National Aeronautics andSpace Administration.

Funding for SDSS-III has been provided by the AlfredP. Sloan Foundation, the Participating Institutions, theNational Science Foundation, and the U.S. Departmentof Energy Office of Science. The SDSS-III web site ishttp://www.sdss3.org/.

SDSS-III is managed by the Astrophysical ResearchConsortium for the Participating Institutions of theSDSS-III Collaboration including the University of Ari-zona, the Brazilian Participation Group, BrookhavenNational Laboratory, Carnegie Mellon University, Uni-versity of Florida, the French Participation Group,the German Participation Group, Harvard University,the Instituto de Astrofisica de Canarias, the MichiganState/Notre Dame/JINA Participation Group, JohnsHopkins University, Lawrence Berkeley National Labora-tory, Max Planck Institute for Astrophysics, Max PlanckInstitute for Extraterrestrial Physics, New Mexico StateUniversity, New York University, Ohio State University,Pennsylvania State University, University of Portsmouth,Princeton University, the Spanish Participation Group,University of Tokyo, University of Utah, Vanderbilt Uni-versity, University of Virginia, University of Washington,and Yale University.

REFERENCES

Abazajian, K., et al. 2004, AJ, 128, 502Abazajian, K., et al. 2005, AJ, 129, 1755Abazajian, K., et al. 2003, AJ, 126, 2081Abazajian, K. N., et al. 2009, ApJS, 182, 543Adelman-McCarthy, J. K., et al. 2008, ApJS, 175, 297Adelman-McCarthy, J. K., et al. 2007, ApJS, 172, 634Adelman-McCarthy, J. K., et al. 2006, ApJS, 162, 38

18

Ahn, C. P., et al. 2012, ApJS, 203, 21Aihara, H., et al. 2011, ApJS, 193, 29Anderson, L., et al. 2013, ArXiv e-prints, 1303.4666Anderson, L., et al. 2012, MNRAS, 427, 3435Annis, J., et al. 2011, ArXiv e-prints, 1111.6619Benjamin, R. A., et al. 2003, PASP, 115, 953Bolton, A. S., et al. 2012, AJ, 144, 144Borucki, W. J., et al. 2010, Science, 327, 977Bovy, J., et al. 2012, ApJ, 759, 131Bressan, A., et al. 2012, MNRAS, 427, 127Bruzual, G., & Charlot, S. 2003, MNRAS, 344, 1000Busca, N. G., et al. 2013, A&A, 552, A96Canterna, R. 1976, AJ, 81, 228Chaplin, W. J., & Miglio, A. 2013, ARA&A, 51, 353Chen, Y.-M., et al. 2012, MNRAS, 421, 314Churchwell, E., et al. 2009, PASP, 121, 213Clark, J. P. A., & McClure, R. D. 1979, PASP, 91, 507Conroy, C., Gunn, J. E., & White, M. 2009, ApJ, 699, 486Cutri, R. M., et al. 2012, Explanatory Supplement to the WISE

All-Sky Data Release Products, Tech. rep.Dawson, K. S., et al. 2013, AJ, 145, 10Eisenstein, D. J., et al. 2001, AJ, 122, 2267Eisenstein, D. J., et al. 2011, AJ, 142, 72Frieman, J. A., et al. 2008, AJ, 135, 338Fukugita, M., et al. 1996, AJ, 111, 1748Garca Perez, A. E., et al. 2013, ApJ, 767, L9Garnett, J. D., et al. 2004, in Society of Photo-Optical

Instrumentation Engineers (SPIE) Conference Series, Vol. 5499,Society of Photo-Optical Instrumentation Engineers (SPIE)Conference Series, ed. J. D. Garnett & J. W. Beletic, 3546

Gilliland, R. L., et al. 2010, PASP, 122, 131Gunn, J. E., et al. 1998, AJ, 116, 3040Gunn, J. E., et al. 2006, AJ, 131, 2332Hekker, S., et al. 2011, A&A, 530, A100Indebetouw, R., et al. 2005, ApJ, 619, 931Ivezic, Z., et al. 2004, Astronomische Nachrichten, 325, 583Komatsu, E., et al. 2011, ApJS, 192, 18Kroupa, P. 2001, MNRAS, 322, 231Lintott, C., et al. 2011, MNRAS, 410, 166Lintott, C. J., et al. 2008, MNRAS, 389, 1179Lupton, R., et al. 2004, PASP, 116, 133

Lupton, R., et al. 2001, in Astronomical Society of the PacificConference Series, Vol. 238, Astronomical Data AnalysisSoftware and Systems X, ed. F. R. Harnden, Jr., F. A. Primini,& H. E. Payne, 269

Majewski, S. R., Ostheimer, J. C., Kunkel, W. E., & Patterson,R. J. 2000, AJ, 120, 2550

Majewski, S. R., Zasowski, G., & Nidever, D. L. 2011, ApJ, 739,25

Maraston, C., et al. 2013, MNRASMaraston, C., & Stromback, G. 2011, MNRAS, 418, 2785Meszaros, S., et al. 2012, AJ, 144, 120Meszaros, S., et al. 2013, AJ, 146, 133Nidever, D. L., et al. 2012, ApJ, 755, L25Padmanabhan, N., et al. 2008, ApJ, 674, 1217Paris, I., et al. 2012, A&A, 548, A66Paris, I., et al. 2013, A&A in press, ArXiv e-prints, 1311.4870Pier, J. R., et al. 2003, AJ, 125, 1559Predehl, P., et al. 2010, in Society of Photo-Optical

Instrumentation Engineers (SPIE) Conference Series, Vol. 7732,Society of Photo-Optical Instrumentation Engineers (SPIE)Conference Series

Richards, G. T., et al. 2002, AJ, 123, 2945Rieke, G. H. 2007, ARA&A, 45, 77Ross, N. P., et al. 2012, ApJS, 199, 3Salpeter, E. E. 1955, ApJ, 121, 161Schneider, D. P., et al. 2010, AJ, 139, 2360Skrutskie, M. F., et al. 2006, AJ, 131, 1163Smee, S. A., et al. 2013, AJ, 146, 32Stoughton, C., et al. 2002, AJ, 123, 485Strauss, M. A., et al. 2002, AJ, 124, 1810Thomas, D., et al. 2013, MNRAS, 431, 1383Tucker, D. L., et al. 2006, Astronomische Nachrichten, 327, 821Wells, D. C., Greisen, E. W., & Harten, R. H. 1981, A&AS, 44,

363Willett, K. W., et al. 2013, MNRAS, 435, 2835Wright, E. L., et al. 2010, AJ, 140, 1868

Yanny, B., et al. 2009, AJ, 137, 4377York, D. G., et al. 2000, AJ, 120, 1579Zasowski, G., et al. 2013, AJ, 146, 81